• International Journal of Contents
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• 제15권3호
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• pp.7-12
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• 2019

The purpose of this study was to analyze characteristics and patterns of 'better class' by using the longitudinal text mining big data analysis technique from subjective lecture evaluation comments. First, this study classified upper 30% classes to deduce certain characteristics and patterns from every five-year subjective text data for 10 years. A total of 47,177courses (100%) from spring semester 2005 to fall semester 2014 were analyzed from a university at a metropolitan city in the mid area of South Korea. This study extracted meaningful words such as good, course, professor, appreciation, lecture, interesting, useful, know, easy, improvement, progress, teaching material, passion, and concern from the order of frequency 2005-2009. The other set of words were class, appreciation, professor, good, course, interesting, understanding, useful, help, student, effort, thinking, not difficult, explanation, lecture, hard, pleasant, easy, study, examination, like, various, fun, and knowledge 2010-2014. This study suggests that the characteristics and patterns of 'better class' at college, should be analyzed according to different academic code such as liberal arts, fine arts, social science, engineering, math and science, and etc.

• 아동학회지
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• 제13권2호
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• pp.53-64
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• 1992

The purpose of the present research was to investigate developmental trends in children's class-inclusion performance and to examine the influence of task characteristics(provision or deprivation of quantitative information and perceptual information) on a class-inclusion task. The subjects of this study were 96 children, 12boys and 12girls at each age level. 5, 6. 7 and 8 years of age. The experimental materials consisted of 12 stimulus boards which were constructed on the basis of picture cards used by Judd and Mervis(1979) and Lane and Hodkin(1985). The class-inclusion tasks were individually administered by the researcher. The data were analyzed by the statistical methods of t-test, one-way ANOVA and Duncan multiple range test. The results showed that (1) There were significant age differences in children's class-inclusion performance. That is, children's performance scores on the class-inclusion task increased with age.: (2) There were significant task characteristics differences in children's class-inclusion performance. That is, children performed better on the deprivation of quantitative information task than on the provision of quantitative information task.

• 전기학회논문지
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• 제59권4호
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• pp.820-822
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• 2010

Mobile WiMAX system provides various classes of traffic such as real-time and non-realtime services. These services have different QoS requirements and the QoS aware scheduling has been an important issue. Although many of scheduling algorithms for various services in OFDMA system have been proposed, it is needed to be modified to be applied to Mobile WiMAX system. Since Mobile WiMAX supports five kinds of service classes, it is important to take QoS characteristics of each class into consideration. In this paper, we propose an efficient packet scheduling algorithm to support QoS of each class. Proposed scheme selects a service class first considering QoS Characteristics of each class and choose an appropriate user in the selected class. Simulation results show that the proposed algorithm has better performance than the other algorithm.

• 보건의료산업학회지
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• 제11권1호
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• pp.131-142
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• 2017

Objectives : This study aimed to examine to relevance of socioeconomic class recognition and subjective health status of injured workers. Methods : We used data collected over 3years by the Panel Study of Worker's Compensation Insurance(PSWCI; 2015). Data was analyzed using the chi-square test and logistic regression using SPSS ver. 22.0 to verify the relevance between the socioeconomic class recognition and general characteristics of injured workers. Results : First, the income groups of first class, second class and third class were analyzed as being of lower socioeconomic class status, and the income group four class and five class was analyzed as being the middle-ower the socioeconomic class status. Second, the better the subjective health status, higher the perception of socioeconomic class status, as analyzed by Model 1 using only the parameters of socioeconomic status recognition and Model 2 and Model 3 using income class and general characteristics. Conclusions : Health and industrial accident policies are needed to improve awareness of socioeconomic class status of injured workers.

• 대한치과교정학회지
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• 제51권1호
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• pp.23-31
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• 2021

Objective: To evaluate the mandibular buccal shelf (MBS) in terms of the angulation and bone depth and thickness according to sex, age, and sagittal and vertical skeletal patterns in a Colombian population using cone-beam computed tomography (CBCT). Accordingly, the optimal site for miniscrew insertion in this area was determined. Methods: This descriptive, retrospective study included 64 hemi-arches of 34 patients. On CBCT images, the angulation, buccal bone depth (4 and 6 mm from the cementoenamel junction [CEJ] of MBS), and buccal bone thickness (6 and 11 mm from the CEJ of MBS) were measured at the mesial and distal roots of the mandibular first and second molars. Results: There were no statistically significant differences in the angulation, depth, and thickness of MBS between male and female patients. The values for the bone around the distal root of the mandibular second molar were significantly greater than the other values. The osseous characteristics were significantly better in participants aged 16-24 years. Class III patients exhibited the best osseous characteristics, with the bone depth at 6 mm being significantly different from that in Class I and Class II patients. Although values tended to be greater in patients with low angles, the difference was not statistically significant. Conclusions: MBS provides an optimal bone surface for miniscrew insertion, with better osseous characteristics at the distal root of the mandibular second molar, 4 mm from CEJ. Adolescent patients, Class III patients, and patients with a low angle exhibit the most favorable osseous characteristics in the MBS area.

• 한국통신학회논문지
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• 제21권3호
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• pp.629-642
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• 1996

ATM switch handles the traffic for a wide range of appliations with different QOS(Quality-of-Service) requirements. In ATM switch, the priority control mechanism is needed to improve effectively the required QOS requirements. In this paper, we propose a priority control mechanism using the cell transfer ratio type and discard threshold in order to archive the cell loss probability requirement and the delay requirement of each service class. The service classes of our concern are the service class with high time priority(class 1) and the service class with high loss priority control mechanism, cells for two kind of service classes are stored and processed within one buffer. In case cells are stored in the buffer, cells for class 2 are allocated in the stored and processed within one buffer. In case cells are stored in the buffer, cells for class 2 are allocated in the shole range of the buffer and cells for class 1 are allocated up to discard threshold of the buffer. In case cells in the buffer are transmitted, one cell for class 1 is transmitted whenever the maximum K cells for class 2 are transmitted consecutively. We analyze the time delay and the loss probability for each class of traffic using Markov chain. The results show that the characteristics of the mean cell delay about cells for class 1 becomes better and that of the cell loss probability about cells for class 2 becomes better by selecting properly discard threshold of the buffer and the cell transfer ratio according to the condition of input traffic.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.243-248
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• 2017

In a basic engineering design class, first year engineering department students learn about engineering design relevant theories and carry out simple projects in teams. By doing a group project in this subject, students develop basic skills such as creativity, teamwork, communication, and problem solving. Before, class proceeded in a way where teams were randomly configured in the beginning of semester and students began working on their project immediately. However, this research introduces a new method where at the beginning of the semester, students are assigned group assignments. Teammates are randomly chosen and constantly switched so that students get a chance to work with different people and experience diverse styles and characteristics. Then, they autonomously form into teams with people they work best and carry out their project. We present the behavior of a monkey robot that recognizes emotions as a case of applying the proposed method. The feedback from the students suggest that this proposed team forming method serves to be effective especially since students who were not aware of other students' characteristics can get to know one another better and form a productive team.

• 전자공학회논문지SC
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• 제38권5호
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• pp.59-69
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• 2001

최근에 디지털 선호처리와 전자부품의 발달로 심음 분식에 관한 많은 연구가 진행되고 있다. 그러나 심음 인식, 특히 심음 한주기 전체에 대한 인식연구는 거의 없다. 본 논문에서 심음 전체 한주기에 대한 새로운 인식 방법을 제안하였다. 먼저 주성분 분석을 이용하여 훈련 셋트로 데이터베이스를 구축한다. 데이터베이스는 새로운 심음입력을 인식하는데 이용된다. 심음은 정상심음, 수축전 심잡음, 수축초기 심잡음, 수축 말기 심잡음, 이완 초기 심잡음, 이완 말기 심잡음， 연속적 심잡음으로 분류된다. 실험결과 새로운 인식 방법은 심음의 특징을 인식하는데 효과적이었다. 최대 인식률은 NO의 경우 71%, PS와 ES의 경우 80%, LS의 경우 78%, ED의 경우 87%, LD의 경우 60%, CM의 경우 20% 이었다. 현재의 결과가 실제적으로 심음을 인식하기에는 충분하지 못하였지만 선음 전체 주기를 대상으로 한 연구라는데 의의가 있으며 더 효과적인 데이터베이스를 구축함으로써 인식률을 개선할 수 있다.

• 한국의류학회지
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• 제26권10호
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• pp.1424-1435
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• 2002

This study is about women's veils from Chosen period housed in various museums and see how they reflect the escalating inequality between the two sexes based on Confucianism and its social ramifications including the strict rules that kept women from freely communicating or staying in same quarters with men from tender age. I first visited various museums to see what kind of veils they had in their collections and then looked at reproductions, museum catalogues, and other studies to get a better understanding of the designs, colors, and fabrics of the veils in each collection and came to following conclusions:. 1. I looked at 26 veils of 7 different sues both in person and in museum catalogues, and they included a Neouls,3 Myunsas, l2Jahngots,4 Chuneuis,1 Sahkgat 3Junmos, and 1 Garima. Various documents attest to the existence of one more style of veil,1. e. skirt-shaped veil, but there was no specimen of the type. 2. Museums had various types of veils for women, but most of them dated from late Chosun period. 3. Female veils in Chosun period had dearly-defined characteristics depending on their wearers. Each type had its own fabric color, and form, so one could tell the status of the wearer just by looking at it 4. The veils that I found at museums around the country had following characteristics: . Neoul was worn by high-class women and it covered up the face better than other types of veils. Myunsa was also caned Myunsapo, and it featured brilliant gold foils to mark the salted status of the wearer. Jahngot was originally a robe for both sexes but it turned into a type of veil for low-class females in late am period and there were more Jangots in museum collections than my other type of veils. Chuneui has various styles and it has a cotton lining so low-class women wore it to both cover the face and to stay worn Sahkgat was worn by low-class women for its convenience. Junmo was elaborately decorated and showy, and it was worn by courtesans. Garima was worn by courtesans or professional women in medicine, and unlike other type of veils, it showed the face of the wearer.

• 한국컴퓨터정보학회논문지
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• 제28권2호
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• pp.9-17
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• 2023

본 논문에서는 베어링의 결함 진단을 위한 단일 클래스 분류의 진동 이상 탐지 시스템을 제안한다. 베어링 고장으로 인해 발생하는 경제적 및 시간적 손실을 줄이기 위해 정확한 결함 진단시스템은 필수적이며 문제 해결을 위해 딥러닝 기반의 결함 진단 시스템들이 널리 연구되고 있다. 그러나 딥러닝 학습을 위한 실제 데이터 채집 환경에서 비정상 데이터 확보에 어려움이 있으며 이는 데이터 편향을 초래한다. 이에 정상 데이터만 활용하는 단일 클래스 분류 방법을 활용한다. 일반적인 방법으로는 AutoEncoder를 통한 압축과 복원 과정을 학습하여 진동 데이터의 특성을 추출한다. 추출된 특성으로 단일 클래스 분류기를 학습하여 이상 탐지를 실시한다. 하지만 이와 같은 방법은 진동 데이터의 주파수 특성을 고려하지 않아서 진동 데이터의 특성을 효율적 추출할 수 없다. 이러한 문제를 해결하기 위해 진동 데이터의 주파수 특성을 고려한 AutoEncoder 모델을 제안한다. 분류 성능은 accuracy 0.910, precision 1.0, recall 0.820, f1-score 0.901이 나왔다. 주파수 특성을 고려한 네트워크 설계로 기존 방법들보다 우수한 성능을 확인하였다.